ABSTRACT In order to obtain speed self-detecting with low cost for a bearingless induction motor (BIM) a speed-sensorless control strategy based on the iterative central difference Kalman filter (ICDKF) is proposed. Firstly, on the basis of the BIM mathematical model, the nonlinear state equation is established and its order is reduced from fifth-order to fourth-order using the stator terminal voltage and current as input. Then, a sterling interpolation formulation is used in the filter to reduce the model error, and an iteration loop link is adopted to improve the filter accuracy. Finally, the online speed of the BIM is identified through the filter rotor speed estimation. Theoretical analysis, simulation and experimental results by UKF and CDKF method have been compared. The results show that the proposed speed-sensorless control system not only has good speed tracking performance and reduce the load disturbance but also improves the BIM suspension performance.

中文翻译：

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基于迭代中心差分卡尔曼滤波器的无轴承感应电机无速度传感器控制系统

摘要 为了以低成本获得无轴承感应电机（BIM）的速度自检测，提出了一种基于迭代中心差分卡尔曼滤波器（ICDKF）的无速度传感器控制策略。首先，在BIM数学模型的基础上，以定子端电压和电流为输入，建立非线性状态方程，将其阶数从五阶降为四阶。然后，在滤波器中使用英镑插值公式来减少模型误差，并采用迭代循环环节来提高滤波器精度。最后，通过过滤器转子速度估计来识别 BIM 的在线速度。比较了UKF和CDKF方法的理论分析、模拟和实验结果。